Journal of Environmental Waste Management and Recycling

An investigation on effective factors on total productivity of water and wastewater industry using multi-criteria decision-making approach (MCDM) (water and Wastewater Company of West Azerbaijan in Iran)

Citation: Alinejad K, Dabbagh R, haghkish N. An investigation on effective factors on total productivity of water and wastewater industry using multicriteria decision-making approach (MCDM) (water and Wastewater Company of West Azerbaijan in Iran). J Environ Waste Management and Recycling. 2018;1(2):8-15

Abstract

Nowadays, labor relations, production, and resource constraints become complicated, and achieving growth in organizations by enhancing productivity accounted as most important goals of countries, therefore productivity improvement activities depend on organizations. The aim of this research is to evaluate and assess total productivity (efficiency + effectiveness) in water and wastewater company of West Azerbaijan estate in Iran during a period from 2005 to 2017. Effectiveness assessed by questionnaire tool using Chi-squared test and Efficiency measured and assessed by a variety of expenses, then they prioritized and weighted using Fuzzy AHP model. Finally, by combining these two indicators, total productivity measured. Results showed that between dimensions of effectiveness, the significance of test in provided services, reducing unwanted results and negative effects, level of knowledge and improvement and promotion of the company was more than 0.05, therefore zero assumption based on independence of these dimensions from gender accepted. Also, significance for dimensions of application of information technology and perception and satisfaction of the customer was 0.001 and 0.018 respectively, which was less than 0.05. This indicates a Relation between these two dimensions and gender of staff. In ranking factors affect efficiency, water costs (0.146) and raw material costs (0.145) variables were prioritized. Over the course, productivity had a lot of fluctuation with an average of 58 units, the reason of which was efficiency reduction in energy and capital, however labor efficiency, and effectiveness indicators had a better status than other indicators and had an improving trend.

Keywords

Effectiveness, Efficiency, Productivity, MCDM, Fuzzy AHP

Introduction

Activities of each organization are affected by a set of
circumstance and factors that needed to be recognized,
investigated and measured to realize goals and optimize
activities effectively. Usually, organizations encounter limits
like shortage of facilities and resources for their activities.
Therefore, they tried to use their limited resources optimally
to be capable of competing their rivals and offer their services
to customers in low cost with high quality. Since resources
are limited and procuring them for organizations is costly,
Therefore, it is necessary to maximize using available resources
to maximize returns [1], which is possible with organizational
efficiency and productivity, because the main goal of
productivity and efficiency is an optimal use of resources and
facilities. Nowadays, researchers and investigators believe that
a country needs capable organizations, systems, human resource
and proper planning and resources to acquire high levels of
productivity and reach their goals. enhancing productivity
is one of the ways to increase production and meet demands
of customer [2]. productivity is measuring the amount of
workforce, energy and other resources in an organization and is
the result of efficiency and effectiveness, in which effectiveness
is yield level, and efficiency is fraction ratio of return on the
given [3]. To achieve high productivity, a certain ceiling cannot
be defined, but companies try to reach the optimized point and see that as their future outlook. In corporations, effectiveness has
outward and efficiency has inward look to activities, therefore
simultaneously computing effectiveness and efficiency and
combining them, make productivity more comprehensive [4].
Sewage network is one of most important infrastructures of
community health that keep fresh water away from pollution.
Water and wastewater companies constitute economy and
industry framework of each country, therefore attending to
their continuous improvement will lead to national productivity
enhance. in recent years, in almost all efforts to study efficiency,
effectiveness, and productivity in corporations, researchers
considered productivity as quantitative “efficiency” or as
qualitative “effectiveness” and these two dimensions are studied
separately. In this study, we investigated productivity “efficiency
+ effectiveness” in urban water and wastewater corporation of
West Azerbaijan in Iran. For this purpose, in the next section,
theoretical foundations and research background and in the third
section method of implementation are introduced. In section
four, results are analyzed and evaluated, and final section a
summary of research presented and suggestions proposed for
future studies.

Productivity

The word “productivity” in different cultures usually expressed
by “processing”, “fertility”, “efficacy”, and “fruition”, and its
general definition is the result of dividing outputs on inputs in a production process. Originally, productivity express proper
use of available resources in production context and it is the
result of dividing outputs on inputs, and with productivity, the
organization will have better production function [5]. According
to International productivity organization, different products
obtained from merging four basic factors of land, capital,
workforce, and productivity defined as the ratio of these factors
on production which is a criterion to measure productivity.
From productivity agency perspective, productivity is level of
effective use from production factors. Considering all of the
definitions above, a general definition of productivity is the
ratio of outputs of a process to its’ inputs. Productivity can be
expressed as two subjects of “efficiency” and “effectiveness”
that are most important factors affect productivity [2].

Effectiveness refers to adjust results of doing the right thing with
desired goals and interests of beneficiaries. In fact, effectiveness
is the degree of achieving predetermined goals that measure
how to achieve the goals. According to theoretical foundations,
effectiveness is concerned with the level of achieving
predetermined goals [6]. Parsons also recognized innovation,
organizational commitment, job satisfaction and organizational
health as effectiveness. French defines effectiveness as the level
of realizing organizational goals [7]. Effectiveness is a process
that drives organizations to assess organizational progress and
achieve organizational goals.

Evaluating effectiveness index requires study of its multiple
dimensions, measuring effectiveness is to measure the
responsiveness of organizations to needs and demands of
customers and citizens. One of these approaches is measuring
provided services to the customer, which is very important and
has a positive effect on society, measuring customer perception
and satisfaction is also one of these dimensions, which play an
important role in the effectiveness of organizations [8,9]. There
is also a close relationship between knowledge management
and organizational effectiveness. importance of acquiring
knowledge is that it makes the organization more effective, avoid
repeating mistakes, reduce the cost and time of accessing to
valuable knowledge within the organization, and transform the
organization into a dynamic, competitive and knowledge-based
organization [10]. The more knowledge-based infrastructure is
reinforced, the more effective role it will play in strengthening
the knowledge management process in the organization, On
the other hand, the optimal and appropriate use of information
technology improve satisfaction, the coherence of programs,
speed of work, and quick response to workflow, which result in
organizational effectiveness [10].

Efficiency is the concept of doing things the right way and
choosing the suitable way of doing things. The goal is to make
optimal use of resources in organizations [2]. Efficiency refers
to a quantitative increase in goods "tangible goods", In other
words, it is defined as the ability to extract more output from
less amount of data. From Chan point of view, efficiency is
the effective use of resources (labor, machinery, capacity, and energy) [11]. Today, there are several methods and techniques to
calculate efficiency, which are chosen according to the purpose
and conditions of the systems. The use of multi-criteria decisionmaking
models make results of calculating efficiency more
scientific, and place the planning process and corrective actions in the context of logical data. In multi-criteria decision making,
instead of using an optimality evaluation method, several
criteria are used, in which structure is based on mathematics
and has high similarity and compatibility with human thinking
and mental processes. In these types of models, the opinion of
experts and managers can be used to make decisions, because
linguistic explanations and considering actual conditions in the
model make the results more accurate and efficient. In another
approach, efficiency is measured by identifying all returns and
dividing them into data, which called total efficiency of all
factors (total efficiency). Also, if efficiency focused on a output,
it is called partial efficiency.

Literature Review

Ashton examined total productivity of the production factors in
the water and wastewater industry in England and Wales with
the Translog model In this study, technical efficiency and total
efficiency of all factors were investigated and results showed
very low levels of efficiency and productivity growth for
all factors [12]. Parhizgari and Gilbert, in a research entitled
"Measuring Effectiveness and Efficiency in Public and Private
Sectors", After identifying and evaluating the effectiveness
and efficiency variables in both public and private sectors by
statistical analysis, compared these two sections. The results
indicate that effectiveness of measures in both the private
and public sectors are significant [13]. Fraquelli and Moiso
have reviewed the cost-effectiveness and economic scale of
the Italian water industry. The results show that in order to
economize the scale of activity and optimize the state of this
industry, scale and size of this industry should be much larger
than the current situation [1]. Marques surveyed the situation
of water and wastewater company in portuguese, introduced a
competitive model for this organization and suggested to use it
in this industry. Also, costs considered as inputs of this model.
Their results showed TFP variations were negative in the period
of study [14]. Guerrini et al. measured the efficiency of the water
and wastewater company in Denmark sewage sector using DEA
method. Results showed low productivity level (The variable
output to scale ratio is 0.48, the static output to scale ratio is
0.36) [15]. Ambalangodage and Yong have conducted a research
called Performance Measurement System (PMS) to improve
performance in the framework of employee participation in Sri
Lanka Water Company. Purpose of this research was to identify
the relationship between employee behavior, organizational
capabilities, and organizational performance. The results showed
a positive relationship between PMS and their participation in the
company [7]. Molinos-Senante et al. investigated productivity
evaluation of Chilean water and wastewater companies for
quality in service delivery using a method of accounting. The
results showed that about one-third of the water and wastewater
companies in Chile are completely efficient [16]. Büyüközkan
and Karabulut examined energy efficiency in Turkey using AHP
method to determine weights and the VIKOR method to rank
options [17]. Tang et al. studied total efficiency and productivity
based on time series data with DEA model in China. Results
showed that total productivity of rural life area factors from
2003 to 2013 was 1.04, which represents a growth rate of 4%.
In addition, the metropolitan area has the highest productivity
in land utilization (an average of 1.023), then Northeastern Environment Conservation Area (1.004), newly developed
urban area (0.998) and environmental protection zone Southeast
(0.997). Also, some indices have decreased in this period and
there has been an increase in some others [18]. Molinos-Senante
et al. surveyed productivity change in water and wastewater
industry in England and Wales using Malmquist index, which
included capital, labor, and energy costs as inputs and volume
of generated water as the output of company in the model.
The results showed that during the period from 2001 to 2014,
productivity level did not improve significantly.

Research Method

This research has an applied type and survey method, and
statistical population in this research was employees of urban
water and wastewater companies in West Azarbaijan province.
Due to the plurality of indicators, both qualitative approach
(data of the questionnaire) and quantitative approach (library
documentation data) are used. pairwise comparison matrix which obtained from the questionnaire and quantitative
information which obtained from water and wastewater
company by collecting experts opinions are used to evaluate
efficiency. According to Table 1, to determine the significance
of each option, an appropriate questionnaire with five-level
fuzzy range prepared and used to define fuzzy numbers in order
to make a comparison.

In order to measure efficiency, factors affect overall efficiency
weighted and prioritized using Fuzzy AHP method. The
hierarchical analysis process is one of the most comprehensive
systems designed for multi-criteria decision making, which
provide a possibility to formulate a problem in a hierarchical
manner, has a capability of using quantitative and qualitative
criteria in decision making, and based on choosing goals and
options and paired comparisons. In this method, it is also
possible to calculate compatibility of decisions and judge its
status. In fact, the AHP method is like human thinking that
makes hard and complex decisions easier.

Fuzzy logic was proposed by Professor Zadeh in 1965 to model
ambiguity and uncertainty in human perception and thought
[19]. Fuzzy characteristics are applicable in many areas of life
that are related to judgment, assessment and decision making
(Figure 1). One of the fuzzy logic related areas is the natural
language in which the meaning of words usually associated
with ambiguity. In fuzzy theory, the membership of the
members set determined by u (x) function, in which x denotes
a distinct member, and u is a fuzzy function that determines the
membership degree of x in the respective set.

Figure 1: Representation of triangular fuzzy numberM1.

For two fuzzy numbers of M1=(l1,m1,u1,) and M2=(l2,m2,u2,), the
operational mathematical rules on fuzzy numbers are defined as:

A fuzzy hierarchy process is a systematic approach that uses
fuzzy sets, multi-criteria decision making, and hierarchical
analysis structure concepts [20]. This method compares the
importance and impact of different factors or options in the
form of a pair comparison questionnaire created by experts or
decision makers. Different members of the matrix of judgment
are fuzzy in the form of a matrix as follow [21].

Now, if there are k experts, integrated opinions matrix of experts
will be obtained from the following relationships:

The result of This integration is a fuzzy matrix, and elements
of this fuzzy matrix are triangular fuzzy numbers which have
respectively the lowest, mean, and the largest value of its
corresponding matrix in pairwise comparison matrix of experts.
Then, using equation (2), fuzzy matrix numbers are compared
with each other.

Given the values obtained in the previous step, the degree of
possibility of calculated over all the other (n - 1) fuzzy
numbers by: (where [21].

j, i = I, L, E, EQ, M, W, S.

To measure effectiveness, data collected using a questionnaire.
To determine the validity of questionnaires and their content,
questionnaires examined by professors as well as experts from
water and Wastewater Company. Based on their views, necessary
and effective changes considered. Finally, the questionnaire was
prepared with a 5 Likert scale for research. According to the
Cochran formula, the sample size was 131 (out of a total of 200
employees). Cronbach's alpha method (with a value of 892)
used To assess the reliability of questionnaire, which showed
high reliability. In order to calculate effectiveness index and
analyze it from data, Chi-squared test was used, which examined
the significant difference between the mean of effectiveness
dimensions and gender. Then, to measure productivity, at first, average effectiveness dimensions and efficiency results of all
factors were standardized on a scale of 0 to 50, and then these
two indices were combined to calculate productivity. SPSS23,
Excel software used to analyze the data.

Analysis of Data

Effectiveness index and its dimensions indicate the amount
of work and activities performed using resources consumed
in water and waste water company. These dimensions
include measuring provided services, measuring perception
and satisfaction of customer, measuring improvement and
promotion of the company, measuring reduction of unwanted
results and negative effects, measuring the knowledge level
and measuring use of information technology. Provided
services include efforts of employees to estimate customer
needs, quality and quantity of distributed water, the pressure
of distributed water, resolve problems by event resolve unit,
and so on. Perceptions and satisfaction of customers include
guiding managers and staff to solve subscribers problems,
comprehensibility of forms and instructions, responding to
complaints of subscribers, the proportionality of provided
information with needs and responding to requests and needs
of subscribers, and so on. Reducing unwanted results and
negative effects dimension in the company defined as pollution
and damage to the environment, costs of low-quality, excess
energy consumption, excessive bureaucracy, and formalities,
etc. Also, using information technology dimension in water
and wastewater Company defined by the level of using
communication network between employees and managers
via the Internet, email, chat, telephone, using company site
for non-attendance services, doing jobs regardless of time
limits set by information tools, travel speed level, information
distribution, etc. Level of knowledge dimension in the company
included sharing knowledge between employees, applying
knowledge in the company, acquiring knowledge, and so on.
Company improvement and promotion dimension defined as
culture promotion in the company, implementation of projects, environmental protection and sanitation, establishing standards
in quality control, protection, safety and health of employees,
and so on. In order to calculate the effectiveness index, first, the
average of effectiveness questionnaire dimensions calculated
and the results are presented in Table 2.

Effectiveness dimensions

Improvement and promotion of company

Knowledge level

Using information technology

Reducing unwanted results and negative effects

Perception and satisfaction of customer

Provided services

average

303/3

805/2

254/3

189/3

588/3

618/3

Table 2. Average of effectiveness indices.

In order to investigate the relationship between the
effectiveness dimensions and gender in case study company,
first, the average amount of each dimension was calculated, then
the relationship between the average of these scores and gender
calculated using chi-square test and the results presented in Table 3.

The significance value of chi-square test in provided
services, reducing unwanted results and negative effects, level
of knowledge and improvement and promotion of company
dimensions was more than 0.05, therefore zero assumption
in which indicate independence of effectiveness dimensions
from the gender of individuals, accepted. Therefore, there was
no difference between various genders of employees in the
effectiveness of activities in water and wastewater company.
These findings mean gender of individuals (men and women)
does not differ significantly in dimensions, and all employees
have an effective and decisive role in this regard.

Significance value in using information technology and
perception and satisfaction of customer dimensions was less
than 0.05, which indicate there are relationships between
genders of individuals with these dimensions. Then using the
Cramer's V test, the intensity of these relationships calculated.

Table 4 shows the results of the Cramer's V test. Decision
criterion for using information technology dimension was 0.001
and for perception and satisfaction of the customer, dimension
was 0.018, which was less than 0.05. This mean, there is a
relationship between gender of staff and these two dimensions.
According to the Table 5, dependence level of a male in the
company is higher than that of the female.

Efficiency Measurement

Making a right strategic decision about choosing a successful
company for investment, require identifying and using criterions
that can provide appropriate distinction indices in this context.
Hence, corporate executives should recognize the condition in
their company and identify factors influence decision-making
process then proceed to plan. Rating costs of the company is
a very important matter that has a determinative and effective
effect in promoting efficiency and productivity. In this research,
judgments of 16 experts from managers and technicians of
the urban water and wastewater company for seven variables
(capital expenditure I, labor costs L, energy costs E, equipment
costs EQ, raw material costs M, water costs W and Sewage sector
costs S) has been shown and prioritized. In order to increase

In Matrix A and other expert opinion matrices, property is maintained. In order to calculate weights for each
of options, combined weights are calculated for each of the
options. To do this, at first, elements of each row of matrix A
calculated using the sum of triangular fuzzy numbers to form a
columnar fuzzy matrix (column x1 in Table 6). Then, elements
of columnar matrix summed up to obtain a fuzzy number (line
x3). This number was reversed (line x4), and then elements of
the columnar matrix (x1) were multiplied by the inverse of the
fuzzy number (x4) to obtain the relative weight of costs (column
x2). The results of these calculations are presented in Table 6.

costs

sum up each row of Matrix A

relative weight of costs (x2)

SI

capital expenditure

(3/1, 7/947, 19)

(0/0238,0/1415,0/8804)

SL

labor costs

(3/16, 7/681, 19)

(0/0243,0/1367,0/8804)

SEQ

energy costs

(2/98, 7/301, 18/5)

(0/0229, 0/1301,0/8572)

SEQ

equipment costs

(3/04, 7/792, 17/5)

(0/0233, 0/1387, 0/8109)

SM

raw material costs

(3/1, 7/803, 18)

(0/0238, 0/1389, 0/8341)

SW

water costs

(3/1, 9/385, 19)

(0/0238, 0/167, 0/8804)

SS

Sewage costs

(3/1, 8/174, 19)

(0/0238, 0/1455, 0/8804)

The sum of the columns of the matrix) x3 (

(21/58, 56/092, 130)

( x4) Inverse the sum of the columns in the matrix

0/0076, 0/0178, 0/0463) )

Table 6. Calculation of weights for each cost.

Now using Equation (4), the relative weights of the costs of the
above table are compared with each other in which and j, i = I, L, E, EQ, M, W, S are defined.

Therefore, we have:

In the following, the importance of options determined
according to (5). Considering values obtained in the previous
step, the smallest amount of possible degree of corresponding
combination size of each of the options being larger than
corresponding combined size of other options selected (after
comparing the values obtained for each cost compared to other
costs, the lowest amount selected). So we have:

After normalizing these costs, final weight of the costs and
their prioritization, presented in Table 7.

costs

final weight

prioritization

Unit water

WW

146/0

1

raw material

WM

145/0

2

wastewater

WS

143/0

3

capital

WI

142/0

4

labor

WL

141/0

5

equipment

WEQ

141/0

6

energy

WE

140/0

7

Table 7. Weights and priorities of costs using the fuzzy method.

According to results of rating company expenses in Table 7,
considering financial constraints of the company and allocating
costs according to ranking can become a tool to control costs
and pay more attention to necessary and unnecessary expenses
incurred in the company without harming main functions of it.
Now, these coefficients can be used to determine intensity and contribution of each cost in total factor efficiency. So we have:

The proposed model used to calculate the total efficiency
of factors using expert's opinions through rating costs (of
production factors) of water and Wastewater Company. Due
to efficiency measurement uniformity, the proposed model
can be used as a general formula for calculating efficiency in
water and wastewater companies and other organizations. The
most important feature of this model against other efficiency
indices is that weights of inputs in the company are not equal,
and their coefficients are not 1. In many organizations and
companies, the importance of different factors varies from
each other. Therefore, the result of considering same weights
in the calculation of efficiency indices may show unrealistic
quality and desirability. Therefore, this model will be able to
analyze the situation in the company by calculating efficiency
more accurately, and it can manage and identify strengths and
weaknesses in the company and create corrective programs to
improve and increase activities. therefore, important issues are
to identify how costs impact the performance of the company
and effective and efficient use of costs in companies how can
improve efficiency and thereby improve productivity.

In order to analyze and assess efficiency, the most appropriate
indices selected based on the definition of efficiency (ratio of
the value of goods and services to expenditures). Considering
the factors of production (labor, capital, and energy), the partial
and total efficiency of the factors investigated. Output value
in the water and waste water company is the sum of values of
employee service compensation, intermediate consumption,
and fix asset consumption. Costs of energy include all energy carriers (electricity, gas, etc.) in terms of monetary unit; also,
capital costs are measured by fixed assets (buildings, facilities,
equipment, incomplete assets, etc.). Labor costs include
salaries, cash, and non-cash benefits, etc, which considered for
each employe.

According to Table 8, total efficiency of factors in the company
fluctuate (0.50 units in 2005, 0.3 units in 2014 and 0.47 units in
2017), in a way that total efficiency average is 0.44 units, and
one of the factors of this decline is capital (with a mean of 0.44
units) and energy efficiency (0.45 units). Also, comparing costs
and output indicate that growth in energy and capital costs is
higher than the value of output in the company.

Efficiency indices

Total Factor Efficiency (TFE)

Energy efficiency

Labor efficiency

Capital efficiency

Year

Output energy costs

Output labor costs

Output capital costs

2005

50/0

40/0

62/0

35/0

2006

55/0

46/0

70/0

42/0

2007

56/0

51/0

67/0

48/0

2008

50/0

49/0

66/0

42/0

2009

51/0

61/0

65/0

44/0

2010

50/0

60/0

57/0

52/0

2011

43/0

64/0

51/0

36/0

2012

46/0

59/0

54/0

48/0

2013

34/0

34/0

71/0

65/0

2014

30/0

36/0

64/0

27/0

2015

30/0

27/0

55/0

37/0

2016

32/0

32/0

45/0

34/0

2017

47/0

45/0

63/0

62/0

Average

44/0

45/0

61/0

44/0

Table 8. Indicators of total and partial efficiency of factors during the period.

Measuring Productivity

To unscale the results of efficiency and effectiveness and sum
up them to calculate the productivity using relationship (Z50=
((x-min)/ (max-min))*50)), all ratios converted to numbers
between 0 and 50 [22] and results presented separately.

It should be noted that due to unscaling of the Figures 1 and 2,
data in the Tables 9 and 10 cannot be analyzed. Total efficiency
and effectiveness indices unscaled in a range from 0 to 50 and
have additive property. Therefore, their composition is feasible,
the results of which are given in Table 11.

Figure 2: Total factor productivity during the course.

Efectiveness dimensions

Improvement and promotion of company

Knowledge level

Using information technology

Reducing unwanted results and negative effects

Perception and satisfaction of customer

Provided services

Average

290/3

889/2

280/3

345/3

570/3

607/3

Average in a scale of 0 to 50

924/27

0

228/27

754/31

423/47

50

Table 9. Converting average of effectiveness indices to a scale of 0 to 50

Year

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

Total efficiency to a scale of 0 to 50

64

35

31

31

37

61

56

69

72

69

81

78

70

Table 10. Converting total factor efficiency index to a scale of 0 to 50.

Year

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

Total Factor productivity

64

35

31

31

37

61

56

69

72

69

81

78

70

Table 11. Total factor productivity during the course.

The productivity level has many fluctuations during the
period (2005 with 70 units, 2014 with 31 units and 2017 with
64 units), in which energy and capital indices, compared to
labor productivity indices, are factors of productivity changes.
Average energy efficiency was 0.45 units, which means energy
efficiency in the current situation has a positive impact on the
provided goods and services but its impact on productivity is low. One of the main reasons for this is that there have been
many changes in energy costs due to rising energy prices over
the years. In order to improve this index, saving energy with new
and upgraded equipment, choosing the best and low-consuming
and technically appropriate equipment in future projects,
optimizing energy consumption equipment in the company is
suggested that reduce costs. The efficiency of labor force with
an average of 0.61 unit has a more significant effect than other
factors on productivity, but to improve this index it is necessary
to employ employees based on their expertise. Also, the average
efficiency of capital was 0.44 units, and to improve this index,
changing capital and investment in the company suggested,
which could improve total efficiency.

Conclusion and Suggestions

To achieve productivity, a certain amount and ceiling cannot be
defined, but what matters is to reach a milestone that companies
are trying to achieve and know it as their prospect. Productivity
is the coordination of quality, quantity, and costs in competition,
and increasing productivity is one way to increase production
and meet demands of people. Productivity measures the status
of labor productivity, capital, energy, and other resources of an
organization, and is the result of efficiency and effectiveness;
effectiveness defined as the level of return, and efficiency is the
ratio of output to data. Effectiveness and efficiency are two main
dimensions of productivity measurement, none of which alone
completes productivity, while in most studies, productivity is
only measured through efficiency. In companies, effectiveness
has an extroverted and efficiency has an introverted look to
activities, therefore calculating efficiency and effectiveness
simultaneously and combining them together make productivity
more comprehensive. Effectiveness results in Urban Water and
Wastewater Company show that the relationship between gender
of employees and the dimensions of effectiveness (knowledge
level, improvement and promotion of the company, reducing
unwanted results and negative effects and provided services)
are known to be independent from gender of individuals.
Hence, there is no difference between genders of individuals
in creating effectiveness in any of these dimensions. However, there is a significant relationship between gender of staff and
use of information technology, and perception and satisfaction
of customer's dimensions, which with Kramer's v test, the
severity of this correlation was respectively obtained 0.93 and
0.85. Inefficiency section, factors affect efficiency prioritized
and weighted using the Fuzzy AHP approach, in which water
costs (with a weight of 0.146) and raw materials (with 0.145)
are in top priority. Then, using obtained weights, a model for
calculating total efficiency presented, which in comparison with
other models that calculate efficiency, has this superiority that
does not take all the inputs of the company into account with
the same importance, and each input introduced(entered) into
model according to its effect. Then partial and total efficiency
of all factors calculated during the period of 2005 to 2017. The
results showed that total efficiency of production factors of the
company had fluctuations; an average efficiency of all factors
with the effect of fuzzy weights was equal to 0.44 units. Reasons
for this decrease are low efficiency in energy and capital sectors.
Level of productivity during the period had a lot of fluctuation
with an average of 58 units, which energy and capital efficiency
indices in comparison with labor efficiency and effectiveness
indices were factors of productivity changes. According to the
results, in order to improve total productivity of the company,
establishing productivity improvement management cycle
(1- productivity measurement, 2-productivity assessment and
analysis, 3- productivity improvement planning, 4-productivity
implementation) suggested. Also, it is suggested that efficiency
indicators for energy (energy saving, equipment optimization,
optimal and low consuming and technically appropriate
equipment selection), capital (capital and investment change),
and labor force (employing employees based on expertise,
creating appropriate ground for innovation and creativity of
staff, continuing job training), to be planned and implemented
as a permanent process according to mechanisms that are
proportionate to situation of company. To allocate appropriate
weights to inputs and outputs for the DEA model using AHP
approach to rank performance, suggested for future research.

References

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